This paper systematically explores the application and technological advancements of embodied intelligence robotics in safety operation and maintenance of large-scale energy storage stations. With energy transition and power system modernization, energy storage stations as critical power infrastructure face numerous operational challenges. The paper analyzes the technical systems of three types of embodied intelligent devices—quadruped robots, wheeled robots, and unmanned aerial vehicles (UAVs)—including environmental perception, state estimation, motion control, gait planning, path optimization, fault detection, and recovery. Through multi-sensor fusion, deep reinforcement learning, improved object detection algorithms, and intelligent control strategies, these robotic systems can achieve efficient and safe autonomous inspection and maintenance in complex and changing energy storage station environments. The study demonstrates that embodied intelligence-based maintenance systems significantly improve station safety operation levels, reduce personnel risks, and enhance fault warning and handling capabilities, providing technical support for the long-term stable operation of energy storage stations. This research has important theoretical and practical value for promoting the application of intelligent robots in power system safety operation and maintenance.